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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate idempotentHint=true and destructiveHint=false. The description adds behavioral context: returns a new subscription id, requires OAuth account, details on delivery channel behavior (webhook signing, auto-disable after 10 failures, SMS cap). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy but well-structured, front-loaded with the main purpose and then expanding into details. While every sentence adds value, it could be more concise by grouping or using bullet points, but the density of information is high.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with nested objects, multiple types, no output schema, and 100% schema coverage, the description compensates fully. It covers examples, constraints, prerequisites, return value, and delivery behavior. The tool is complex, and the description leaves no gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds significant value beyond the schema. For 'type', it explains each enum value with real examples. For 'params', it provides per-type JSON structures. For 'delivery', it adds behavioral details (e.g., webhook signing, SMS verification requirement, cap).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it creates a proactive monitoring subscription to a live-data event stream, using the verb 'Create' and specifying the resource. It distinguishes from sibling tools like 'unsubscribe' and 'list_subscriptions'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use the tool (proactive monitoring), supported types with detailed examples, delivery channels, prerequisites (OAuth account, phone verification for SMS), and constraints (SMS cap, webhook auto-disable). No alternatives explicitly named, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all route factual questions through similar pipelines. The polymarket_* cluster also blurs together, with arbitrage, edges, fill_risk, kalshi_spread, and bet_research all analyzing prediction-market mispricings from different angles.

Naming Consistency3/5

All names use consistent snake_case, but the verb/noun pattern is mixed: some are verb-first (compare_entities, generate_llms_txt, validate_claim), others noun-first (polymarket_edges, entity_profile, ai_visibility_check), and some are bare product names (ask_pipeworx, pipeworx_trending). Readable overall, but no single predictable convention.

Tool Count2/5

34 tools is far too many for a coherent server, especially since the server is named 'Sgd' but only 3 tools relate to yeast genetics. The remaining 31 tools span data lookup, prediction markets, memory, subscriptions, npm scanning, and llms.txt generation—an unfocused grab bag that should be split into multiple servers.

Completeness2/5

As an SGD yeast-genome server, the surface is thin: search, get_gene, and get_gene_go cover basic lookup but miss sequences, interactions, strains, homologs, and other standard SGD data. As a general data utility, the collection is broad but incoherent, with several one-off tools (generate_llms_txt, scan_dependency) that have no connection to the rest.